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Carbon use efficiency (CUE) is a fundamental parameter for ecological models based on the physiology of microorganisms. CUE determines energy and material flows to higher trophic levels, conversion of plantproduced carbon into microbial products and rates of ecosystem carbon storage. Thermodynamic calculations support a maximum CUE value of~0.60 (CUE max ). Kinetic and stoichiometric constraints on microbial growth suggest that CUE in multi-resource limited natural systems should approach~0.3 (CUE max /2). However, the mean CUE values reported for aquatic and terrestrial ecosystems differ by twofold (~0.26 vs.~0.55) because the methods used to estimate CUE in aquatic and terrestrial systems generally differ and soil estimates are less likely to capture the full maintenance costs of community metabolism given the difficulty of measurements in water-limited environments. Moreover, many simulation models lack adequate representation of energy spilling pathways and stoichiometric constraints on metabolism, which can also lead to overestimates of CUE. We recommend that broad-scale models use a CUE value of 0.30, unless there is evidence for lower values as a result of pervasive nutrient limitations. Ecosystem models operating at finer scales should consider resource composition, stoichiometric constraints and biomass composition, as well as environmental drivers, to predict the CUE of microbial communities.

Despite the central role of microorganisms in the decomposition of dead organic matter, few models have integrated the dynamics of litter chemistry with microbial interactions. Here we propose a functional resolution of the microbial community that parallels the commonly used chemical characterization of plant litter, i.e., a guild of opportunist microorganisms that grows quickly and has high affinity for soluble substrates, a guild of decomposer specialists that grows more slowly and has high affinity for holocellulose substrates, and a guild of miners that grows very slowly and is specialized for degrading lignin. This guild‐based decomposition model (GDM) includes the interactions of holocellulose and lignin, manifest as mutual feedback controls on microbial‐based activities. It also includes N limitations on early stages of litter decay resulting from nutritional demands of microorganisms and N inhibition on late stages of litter decay resulting from reduced lignin degradation. Competitive interactions between microbial guilds result from different growth rates and substrate affinities, given limits on microbial colonization of litter. Simulations are consistent with commonly reported and proposed patterns of microbial community succession during litter decay, changes in and controls imposed by litter chemistry, and system responses to N availability. Modest impacts of litter chemistry and N effects on patterns of decay can yield substantial impacts on the relative amount of litter remaining through time, the time required to stabilize litter carbon (i.e., as the lignin content approaches Ìf70% of the total litter carbon), the relative contributions of different guilds to decay, and the net amount of microbial production. Moreover, seemingly inconsistent patterns in system responses to N regimes can be explained by interactions between litter chemistry and microbial guilds. A validation exercise demonstrated general correspondence of model behavior to field observations. However, relationships among mass loss, litter chemistry, and N availability were more variable in field studies than in simulations. Also, observed changes in litter quality indicated the progressive accumulation of microbial products. Hence, field studies suggest expanding GDM to include dynamics of microbial products and also suggest the utility of GDM in exploring site effects on decomposition as a result of differences in microbial community composition.

The average air temperature at the Earth's surface has increased by 0.06 degrees C per decade during the 20th century, and by 0.19 degrees C per decade from 1979 to 1998. Climate models generally predict amplified warming in polar regions, as observed in Antarctica's peninsula region over the second half of the 20th century. Although previous reports suggest slight recent continental warming, our spatial analysis of Antarctic meteorological data demonstrates a net cooling on the Antarctic continent between 1966 and 2000, particularly during summer and autumn. The McMurdo Dry Valleys have cooled by 0.7 degrees C per decade between 1986 and 2000, with similar pronounced seasonal trends. Summer cooling is particularly important to Antarctic terrestrial ecosystems that are poised at the interface of ice and water. Here we present data from the dry valleys representing evidence of rapid terrestrial ecosystem response to climate cooling in Antarctica, including decreased primary productivity of lakes (6-9% per year) and declining numbers of soil invertebrates (more than 10% per year). Continental Antarctic cooling, especially the seasonality of cooling, poses challenges to models of climate and ecosystem change.

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Abstract. The carbon use efficiency (CUE) of microbial communities partitions the flow of C from primary producers to the atmosphere, decomposer food webs and soil C stores. CUE, usually defined as the ratio of growth to assimilation, is a critical parameter in ecosystem models, but is seldom measured directly in soils because of the methodological difficulty of measuring in situ rates of microbial growth and respiration. Alternatively, CUE can be estimated indirectly from the elemental stoichiometry of organic matter and microbial biomass, and the ratios of C to nutrient-acquiring ecoenzymatic activities. We used this approach to estimate and compare microbial CUE in >2000 soils from a broad range of ecosystems. Mean CUE based on C:N stoichiometry was 0.269 ± 0.110 (SD). A parallel calculation based on C:P stoichiometry yielded a mean CUE estimate of 0.252 ± 0.125 (SD). The mean values and frequency distributions were similar to those from aquatic ecosystems, also calculated from stoichiometric models, and to those calculated from direct measurements of bacterial and fungal growth and respiration. CUE was directly related to microbial biomass C with a scaling exponent of 0.304 ± 0.067 (95% CI) and inversely related to microbial biomass P with a scaling exponent of -0.234 ± 0.055 (95% CI). Relative to CUE, biomass specific turnover time increased with a scaling Accepted ArticleThis article is protected by copyright. All rights reserved. exponent of 0.509 ± 0.042. CUE increased weakly with mean annual temperature. CUE declined with increasing soil pH reaching a minimum at pH 7.0, then increased again as soil pH approached 9.0, a pattern consistent with pH trends in the ratio of fungal:bacteria abundance and growth. Structural equation models that related geographic variables to CUE component variables showed the strongest connections for paths linking latitude and pH to ß-glucosidase activity and soil C:N:P ratios. The integration of stoichiometric and metabolic models provides a quantitative description of the functional organization of soil microbial communities that can improve the representation of CUE in microbial process and ecosystem simulation models.

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